Biogeochemical carbon coupling influences global precipitation in geoengineering experiments
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Climate model studies in which CO 2 ‐induced global warming is offset by engineered decreases of incoming solar radiation are generally robust in their prediction of reduced amounts of global precipitation. While this precipitation response has been explained on the basis of changes in net radiation controlling evaporative processes at the surface, there has been relatively little consideration of the relative role of biogeochemical carbon‐cycle interactions. To address this issue, we employ an Earth System Model that includes oceanic and terrestrial carbon components to isolate the impact of biogeochemical carbon coupling on the precipitation response in geoengineering experiments for two types of solar radiation management. We show that carbon coupling is responsible for a large fraction of the global precipitation reduction in such geoengineering experiments and that the primary effect comes from reduced transpiration through the leaves of plants and trees in the terrestrial component of the carbon cycle due to elevated CO 2 . Our results suggest that biogeochemical interactions are as important as changes in net radiation and that climate models that do not account for such carbon coupling may significantly underestimate precipitation reductions in a geoengineered world.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it